Technologies:

.NET / ASP.NET Framework / AWS / MS SQL / Serenity

About the client

Our client is a FinTech company from Phoenix, Arizona that provides SaaS lending solutions for borrowers and banks. Our client’s product helps end customers meet the financial needs of their private businesses by offering financial services including credit scores, wide lines of credit, merchant cash advance, equipment borrowing, and business loans. The main advantage of their SaaS lending platform is that it handles everything in one place — from borrower evaluation to actual money transactions — without special personal guarantees or notarized documents.

Our client came with the challenge

Our client had experienced limitations with their in-house engineering capacity, which is why they had been looking for an engineering partner to develop SaaS lending software. They found one a year ago but eventually stopped cooperation with the vendor because of quality and scheduling issues.

Our client needed to move fast to avoid delays and was looking for an experienced partner with deep expertise in FinTech and SaaS banking software platform development that could grasp their idea quickly. They needed to continue development and eventually increase productivity to catch up with a backlog remaining after the previous vendor; after all, they still needed to develop both backend and frontend parts of the solution.

Our client was already familiar with Ukraine as one of the most prominent outsourcing destinations in Eastern Europe, and they found the right match with Intellias quickly. Our cooperation started smoothly with constant knowledge sharing sessions involving the client’s team and Intellias engineers.

Intellias developed the solution

The cooperation started with three engineers on our side, but soon the Intellias team had grown twofold – and it still continues growing to deliver client’s SaaS banking platform. Our team is involved in most engineering processes and is covering the entire backend development for the SaaS lending solution. This solution collects data from borrowers about their credit history, other loans, and the business in which they will invest. Ultimately, our client’s lending solution is a bridge between individuals who are looking for funds to grow their businesses and established banks that can provide money to meet their financial needs.

After forming a comprehensive borrower profile, the system performs the first round of borrower qualification and calculates the credit score of each borrower. The process of a new borrower onboarding and verification ends up with the primary decision on the user’s access to the system – yes or no. If a potential borrower’s credit score matches predetermined criteria, the loan request is redirected to a bank that can make a verification call if needed.

The process of getting a loan is simple and doesn’t require a lot of documents from the borrower. Here’s the only data that borrowers need to provide:

An application for business funding

A valid business license

Two months’ worth of bank statements

A valid driver’s license

The Intellias team is also involved in the development of a credit score calculator that lets borrowers clearly calculate how much money they’ll pay with interest and what is the possibility to get a loan. We introduced the set of rules that analyzes 3-Bureau Credit Reports information gathered via third-party services (Identity Management Platform) and decides whether to give money to the borrower or not and what is a possible amount. The platform classifies borrowers based on 3-Bureau Credit Reports data by different Tiers. According to Tier level, the platform proposes the amount of loan. Currently, the biggest amount is $100K, and it changes by $25K depending on the Tier level.

We’ve also developed AWS-based fault-tolerant databases to get the most useful insights from data collected on borrowers and their businesses. Then we decided to use collected data as a basis for the machine learning component. We use it for the calculator to make data-driven decisions on loans. The client plans to use this machine learning functionality for small amounts of loans to give money automatically based on borrower’s data and ML algorithms.

Our client’s solution can be integrated with third-party servers using an API. For now, it can be integrated with several popular services:

We’ve achieved great results together

After almost half a year of cooperation, our Intellias team is covering all engineering processes for the SaaS lending platform that qualifies potential borrowers and manages the entire loan lifecycle. We’ve created a personal accounts system for collecting data and a user-friendly calculator to calculate loan payments. The system includes a recording of verification calls from a bank to a potential borrower, a sustainable database that can withstand fast aggregation of huge data volumes, and easy integration options.

Now that the first release has been successfully delivered, we’re continuing to improve the solution. We’re preparing updates for user reports and, most importantly, improving visualization of collected data so it can be used for more insightful decision-making. Our collaboration is growing as we fix bugs and deliver new features in addition to providing continuous support for the released version of the platform. The system works smoothly and provides business owners with instant loans so they can realize their ideas. The next steps we have planned include implementing machine learning algorithms to improve the speed and usefulness of credit scores.

Our client’s SaaS solution for lending provides the following benefits to business owners:

Loan qualification for amounts up to $100,000

No pre-payment penalties for borrowers

Possibility to choose the pace of payments

Support for startups as early as two months after they’re formed

Business credit to establish ideas fast without worrying about capital at the beginning

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